Imposing Motion Variability for Ergonomic Human-Robot Collaboration.

OCCUPATIONAL APPLICATIONS"Overassistive" robots can adversely impact long-term human-robot collaboration in the workplace, leading to risks of worker complacency, reduced workforce skill sets, and diminished situational awareness. Ergonomics practitioners should thus be cautious about solely targeting widely adopted metrics for improving human-robot collaboration, such as user trust and comfort. By contrast, introducing variability and adaptation into a collaborative robot's behavior could prove vital in preventing the negative consequences of overreliance and overtrust in an autonomous partner.

Multimodal fusion of EMG and vision for human grasp intent inference in prosthetic hand control.

For transradial amputees, robotic prosthetic hands promise to regain the capability to perform daily living activities. Current control methods based on physiological signals such as electromyography (EMG) are prone to yielding poor inference outcomes due to motion artifacts, muscle fatigue, and many more. Vision sensors are a major source of information about the environment state and can play a vital role in inferring feasible and intended gestures.

Occluded object detection and exposure in cluttered environments with automated hyperspectral anomaly detection.

Cluttered environments with partial object occlusions pose significant challenges to robot manipulation. In settings composed of one dominant object type and various undesirable contaminants, occlusions make it difficult to both recognize and isolate undesirable objects. Spatial features alone are not always sufficiently distinct to reliably identify anomalies under multiple layers of clutter, with only a fractional part of the object exposed.

Motion Polytopes in Virtual Reality for Shared Control in Remote Manipulation Applications.

In remote applications that mandate human supervision, shared control can prove vital by establishing a harmonious balance between the high-level cognition of a user and the low-level autonomy of a robot. Though in practice, achieving this balance is a challenging endeavor that largely depends on whether the operator effectively interprets the underlying shared control. Inspired by recent works on using immersive technologies to expose the internal shared control, we develop a virtual reality system to visually guide human-in-the-loop manipulation.

A Holistic Approach to Human-Supervised Humanoid Robot Operations in Extreme Environments.

Nuclear energy will play a critical role in meeting clean energy targets worldwide. However, nuclear environments are dangerous for humans to operate in due to the presence of highly radioactive materials. Robots can help address this issue by allowing remote access to nuclear and other highly hazardous facilities under human supervision to perform inspection and maintenance tasks during normal operations, help with clean-up missions, and aid in decommissioning.

HANDS: a multimodal dataset for modeling toward human grasp intent inference in prosthetic hands.

Upper limb and hand functionality is critical to many activities of daily living and the amputation of one can lead to significant functionality loss for individuals. From this perspective, advanced prosthetic hands of the future are anticipated to benefit from improved shared control between a robotic hand and its human user, but more importantly from the improved capability to infer human intent from multimodal sensor data to provide the robotic hand perception abilities regarding the operational context. Such multimodal sensor data may include various environment sensors including vision, as well as human physiology and behavior sensors including electromyography and inertial measurement units.

Human-centered design of a cyber-physical system for advanced response to Ebola (CARE).

We describe the process towards the design of a safe, reliable, and intuitive emergency treatment unit to facilitate a higher degree of safety and situational awareness for medical staff, leading to an increased level of patient care during an epidemic outbreak in an unprepared, underdeveloped, or disaster stricken area. We start with a human-centered design process to understand the design challenge of working with Ebola treatment units in Western Africa in the latest Ebola outbreak, and show preliminary work towards cyber-physical technologies applicable to potentially helping during the next outbreak.

User-centric design of a personal assistance robot (FRASIER) for active aging.

We present our preliminary results from the design process for developing the Worcester Polytechnic Institute's personal assistance robot, FRASIER, as an intelligent service robot for enabling active aging. The robot capabilities include vision-based object detection, tracking the user and help with carrying heavy items such as grocery bags or cafeteria trays. This work-in-progress report outlines our motivation and approach to developing the next generation of service robots for the elderly.

Towards personalized smart wheelchairs: Lessons learned from discovery interviews.

We posit that it is necessary to investigate the personalization of smart wheelchairs in three aspects interfaces for interaction, controllers for action (top-level, middle-level, and low-level), and feedback in interaction. Our team has been selected as an Innovation Corps (I-Corps) Team by the National Science Foundation to pursue customer discovery research to explore the commercial viability of smart wheelchairs. Through the process, our team has performed more than 110 interviews with powered wheelchair users, manufacturers, therapists, policy makers, and non-profit organization staff.

Robot-assisted home hazard assessment for fall prevention: a feasibility study.

We examined the feasibility of using a remotely manoeuverable robot to make home hazard assessments for fall prevention. We employed use-case simulations to compare robot assessments with in-person assessments. We screened the homes of nine elderly patients (aged 65 years or more) for fall risks using the HEROS screening assessment.

A taxonomy for user-healthcare robot interaction.

This paper evaluates existing taxonomies aimed at characterizing the interaction between robots and their users and modifies them for health care applications. The modifications are based on existing robot technologies and user acceptance of robotics. Characterization of the user, or in this case the patient, is a primary focus of the paper, as they present a unique new role as robot users.